Supply Chain Engineering Intern, Data Analytics
About Our Group The Supply Chain Engineering team at Seagate partners closely with internal functions and external suppliers to ensure materials and components meet the company's quality, reliability, and cost objectives. The team plays a key role in enabling efficient, sustainable, and high-performing supply chain operations. We are passionate about improving processes through data-driven insights and engineering principles. By optimizing materials, supplier performance, and manufacturing processes, the team contributes directly to Seagate's sustainability goals and operational excellence. About The Role - You Will As a Supply Chain Engineering Intern, you will support data-driven initiatives to improve supplier quality and supply chain performance. You will gain hands-on experience in analytics, problem-solving, and cross-functional collaboration.
- Collect, clean, and analyze data related to supplier quality metrics (e.g., process variation and contamination trends)
- Support development of dashboards and reports to monitor supplier performance using tools such as Power BI or similar platforms
- Apply basic predictive analytics or modeling techniques to explore relationships between supplier data and product performance
- Assist in identifying trends and presenting insights on supplier quality issues to stakeholders
- Participate in root cause analysis for supplier-related issues and support corrective/preventive actions
- Collaborate with suppliers and internal teams (e.g., manufacturing, quality, engineering) to improve component quality and reduce cost
- Review component qualification data and support documentation for compliance and traceability
- Contribute to continuous improvement initiatives in supplier processes and manufacturing operations
- Curious and eager to learn about supply chain engineering and data analytics
- A strong team player with good interpersonal and communication skills
- Detail-oriented with a structured approach to problem-solving
- Comfortable working with data and presenting insights clearly
- Open to feedback and willing to take initiative in a fast-paced environment
- Currently pursuing an Bachelor degree in Data Science, Analytics, Engineering, or a related field
- Familiarity with data analysis tools such as SQL, Power BI, JMP, Python, or similar platforms
- Basic understanding of quality control principles and continuous improvement methodologies (e.g., Six Sigma concepts)
- Exposure to data visualization and reporting techniques
- Interest in applying analytics within an engineering or supply chain context